M
M-J. Yvonne Ou
Publications - 7
Citations - 153
M-J. Yvonne Ou is an academic researcher. The author has contributed to research in topics: Computer science & Multiresolution analysis. The author has an hindex of 2, co-authored 2 publications receiving 129 citations.
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MADNESS: A Multiresolution, Adaptive Numerical Environment for Scientific Simulation
Robert W. Harrison,Gregory Beylkin,Florian A. Bischoff,Justus A. Calvin,George I. Fann,Jacob Fosso-Tande,Diego Galindo,Jeff R. Hammond,Rebecca Hartman-Baker,Judith Hill,Jun Jia,Jakob S. Kottmann,M-J. Yvonne Ou,Laura E. Ratcliff,Matthew G. Reuter,Adam Richie-Halford,Nichols A. Romero,Hideo Sekino,William A. Shelton,Bryan Sundahl,W. Scott Thornton,Edward F. Valeev,Álvaro Vázquez-Mayagoitia,Nicholas Vence,Yukina Yokoi +24 more
TL;DR: The features and capabilities of MADNESS are described and some current applications in chemistry and several areas of physics are discussed.
Journal ArticleDOI
MADNESS: A Multiresolution, Adaptive Numerical Environment for Scientific Simulation
Robert W. Harrison,Gregory Beylkin,Florian A. Bischoff,Justus A. Calvin,George I. Fann,Jacob Fosso-Tande,Diego Galindo,Jeff R. Hammond,Rebecca Hartman-Baker,Judith Hill,Jun Jia,Jakob S. Kottmann,M-J. Yvonne Ou,Junchen Pei,Laura E. Ratcliff,Matthew G. Reuter,Adam Richie-Halford,Nichols A. Romero,Hideo Sekino,William A. Shelton,Bryan Sundahl,W. Scott Thornton,Edward F. Valeev,Álvaro Vázquez-Mayagoitia,Nicholas Vence,Takeshi Yanai,Yukina Yokoi +26 more
TL;DR: The MADNESS (multiresolution adaptive numerical environment for scientific simulation) as mentioned in this paper is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods with guaranteed precision that are based on multiresolution analysis and separated representations.
Journal ArticleDOI
An adaptive RKHS regularization for Fredholm integral equations
Fei Lu,M-J. Yvonne Ou +1 more
TL;DR: In this paper , the authors proposed a regularization algorithm for ill-posed linear inverse problems based on the Fredholm integral equation of the first kind (RKHS), and proved that the RKHS-regularized estimator has a mean-square error converging linearly as the noise scale decreases, with a multiplicative factor smaller than the commonly-used $L 2 -regularizer.
Journal ArticleDOI
Span of regularization for solution of inverse problems with application to magnetic resonance relaxometry of the brain
TL;DR: SpanReg as discussed by the authors is a regularization method for the solution of the Fredholm integral equation of the first kind, in which they incorporate solutions corresponding to a range of Tikhonov regularizers into the end result.
Journal ArticleDOI
On the time-domain full waveform inversion for time-dissipative and dispersive poroelastic media
TL;DR: In this article , the forward problem is formulated as a minimization problem of a least-square misfit function with the (IBVP) as the constraint, and the adjoint problem is derived to computed the direction of steepest descent in the iterative process for minimization.